Virtual Therapy with the NMDA Antagonist Memantine in Hippocampal Models of Moderate to Severe Alzheimer's Disease, in Silico Trials.

The variability in clinical trial results on memantine treatment of Alzheimer's disease remains incompletely explained. The aim of this in silico study is a virtual memantine therapy for Alzheimer's disease that provides a different perspective on clinical trials; An in silico randomised trial using virtual hippocampi to treat moderate to severe Alzheimer's disease with doses of memantine 3-30 µM compared to placebo. The primary endpoint was the number of impulses (spikes). Secondary endpoints included interspike interval and frequency; The number of virtual moderate-AD hippocampal spikes was significantly lower, at 1648.7 (95% CI, 1344.5-1952.9), versus those treated with the 3 µM dose, 2324.7 (95% CI, 2045.9-2603.5), and the 10 µM dose, 3607.0 (95% CI, 3137.6-4076.4). In contrast, the number of virtual spikes (spikes) of severe AD of the hippocampus was significantly lower, at 1461.8 (95% CI, 1196.2-1727.4), versus those treated with the 10 µM dose, at 2734.5 (95% CI, 2369.8-3099.2), and the 30 µM dose, at 3748.9 (95% CI, 3219.8-4278.0). The results of the analysis of secondary endpoints, interspike intervals and frequencies changed statistically significantly relative to the placebo; The results of the in silico study confirm that memantine monotherapy is effective in the treatment of moderate to severe Alzheimer's disease, as assessed by various neuronal parameters.

The Computer Simulation of Therapy with the NMDA Antagonist in Excitotoxic Neurodegeneration in an Alzheimer's Disease-like Pathology.

(1) Background: The use of uncompetitive N-methyl-D-aspartate (NMDA) receptor antagonists results in neuroprotective benefits in patients with moderate to severe Alzheimer's disease. In this study, we demonstrated mathematical and computer modelling of the excitotoxicity phenomenon and performed virtual memantine therapy. (2) Methods: A computer simulation environment of the N-methyl-D-aspartate receptor combining biological mechanisms of channel activation by means of excessive extracellular glutamic acid concentration in three models of excitotoxicity severity. The simulation model is based on sliding register tables, where each table is associated with corresponding synaptic inputs. Modelling of the increase in extracellular glutamate concentration, through over-stimulation of NMDA receptors and exacerbation of excitotoxicity, is performed by gradually increasing the parameters of phenomenological events by the power function. Pathological models were virtually treated with 3−30 µM doses of memantine compared to controls. (3) Results: The virtual therapy results of memantine at doses of 3−30 µM in the pathological models of excitotoxicity severity show statistically significant neuroprotective benefits in AD patients with moderate severity, 1.25 (95% CI, 1.18−1.32) vs. 1.76 (95% CI, 1.71−1.80) vs. 1.53 (95% CI, 1.48−1.59), (p < 0.001), to severe, 1.32 (95% CI, 1.12−1.53) vs. 1.77 (95% CI, 1.72−1.82) vs. 1.73 (95% CI, 1.68−1.79), (p < 0.001), in the area of effects on memory. A statistically significant benefit of memantine was demonstrated for all neuronal parameters in pathological models. In the mild severity model, a statistically significant increase in frequency was obtained relative to virtual memantine treatment with a dose of 3 µM, which was 23.5 Hz (95% CI, 15.5−28.4) vs. 38.8 Hz (95% CI, 34.0−43.6), (p < 0.0001). In the intermediate excitotoxicity severity model, a statistically significant increase in frequency was obtained relative to virtual memantine therapy with a 3 µM dose of 26.0 Hz (95% CI, 15.7−36.2) vs. 39.0 Hz (95% CI, 34.2−43.8) and a 10 µM dose of 26.0 Hz (95% CI, 15.7−36.2) vs. 30.9 Hz (95% CI, 26.4−35.4), (p < 0.0001). A statistically significant increase in frequency was obtained in the advanced excitotoxicity severity model as in the medium. (4) Conclusions: The NMDA antagonist memantine causes neuroprotective benefits in patients with moderate to severe AD. One of the most important benefits of memantine is the improvement of cognitive function and beneficial effects on memory. On the other hand, memantine provides only symptomatic and temporary support for AD patients. Memantine is prescribed in the US and Europe if a patient has moderate to severe AD. Memantine has also been approved for mild to moderate AD patients. However, its very modest effect provides motivation for further research into new drugs in AD. We are the first to present a mathematical model of the NMDA receptor that allows the simulation of excitotoxicity and virtual memantine therapy.

Computer Modeling of Alzheimer's Disease-Simulations of Synaptic Plasticity and Memory in the CA3-CA1 Hippocampal Formation Microcircuit.

This paper aims to present computer modeling of synaptic plasticity and memory in the CA3-CA1 hippocampal formation microcircuit. The computer simulations showed a comparison of a pathological model in which Alzheimer's disease (AD) was simulated by synaptic degradation in the hippocampus and control model (healthy) of CA3-CA1 networks with modification of weights for the memory. There were statistically higher spike values of both CA1 and CA3 pyramidal cells in the control model than in the pathological model (p = 0.0042 for CA1 and p = 0.0033 for CA3). A similar outcome was achieved for frequency (p = 0.0002 for CA1 and p = 0.0001 for CA3). The entropy of pyramidal cells of the healthy CA3 network seemed to be significantly higher than that of AD (p = 0.0304). We need to study a lot of physiological parameters and their combinations of the CA3-CA1 hippocampal formation microcircuit to understand AD. High statistically correlations were obtained between memory, spikes and synaptic deletion in both CA1 and CA3 cells.

Application of Artificial Neural Networks to Identify Alzheimer's Disease Using Cerebral Perfusion SPECT Data.

The aim of this study was to demonstrate the usefulness of artificial neural networks in Alzheimer disease diagnosis (AD) using data of brain single photon emission computed tomography (SPECT). The results were compared with discriminant analysis. The study population consisted of 132 clinically diagnosed patients. There were 72 subjects with AD and 60 belonging to the normal control group. The artificial neural network used 36 numerical values being the count numbers obtained for each area of brain SPECT. These numbers determined the set of input data for the artificial neural network. The sensitivity of Alzheimer disease diagnosis detection by artificial neural network and discriminant analysis were 93.8% and 86.1%, respectively, and the corresponding specificity was 100% and 95%. We also used receiver operating characteristic curve (ROC) analysis and areas under receiver operating characteristics curves were correspondingly 0.97 (p < 0.0001) for the artificial neural networks (ANN) and 0.96 (p < 0.0001) for discriminant analysis. In conclusion, artificial neural networks and conventional statistics methods (discriminant analysis) are a useful tool in Alzheimer disease diagnosis.

Computer Model of Synapse Loss During an Alzheimer's Disease-Like Pathology in Hippocampal Subregions DG, CA3 and CA1-The Way to Chaos and Information Transfer.

The aim of the study was to compare the computer model of synaptic breakdown in an Alzheimer's disease-like pathology in the dentate gyrus (DG), CA3 and CA1 regions of the hippocampus with a control model using neuronal parameters and methods describing the complexity of the system, such as the correlative dimension, Shannon entropy and positive maximal Lyapunov exponent. The model of synaptic breakdown (from 13% to 50%) in the hippocampus modeling the dynamics of an Alzheimer's disease-like pathology was simulated. Modeling consisted in turning off one after the other EC2 connections and connections from the dentate gyrus on the CA3 pyramidal neurons. The pathological model of synaptic disintegration was compared to a control. The larger synaptic breakdown was associated with a statistically significant decrease in the number of spikes (R = -0.79, P < 0.001), spikes per burst (R = -0.76, P < 0.001) and burst duration (R = -0.83, P < 0.001) and an increase in the inter-burst interval (R = 0.85, P < 0.001) in DG-CA3-CA1. The positive maximal Lyapunov exponent in the control model was negative, but in the pathological model had a positive value of DG-CA3-CA1. A statistically significant decrease of Shannon entropy with the direction of information flow DG->CA3->CA1 (R = -0.79, P < 0.001) in the pathological model and a statistically significant increase with greater synaptic breakdown (R = 0.24, P < 0.05) of the CA3-CA1 region was obtained. The reduction of entropy transfer for DG->CA3 at the level of synaptic breakdown of 35% was 35%, compared with the control. Entropy transfer for CA3->CA1 at the level of synaptic breakdown of 35% increased to 95% relative to the control. The synaptic breakdown model in an Alzheimer's disease-like pathology in DG-CA3-CA1 exhibits chaotic features as opposed to the control. Synaptic breakdown in which an increase of Shannon entropy is observed indicates an irreversible process of Alzheimer's disease. The increase in synapse loss resulted in decreased information flow and entropy transfer in DG->CA3, and at the same time a strong increase in CA3->CA1.

Effects of Inducing Gamma Oscillations in Hippocampal Subregions DG, CA3, and CA1 on the Potential Alleviation of Alzheimer's Disease-Related Pathology: Computer Modeling and Simulations.

The aim of this study was to evaluate the possibility of the gamma oscillation function (40-130 Hz) to reduce Alzheimer's disease related pathology in a computer model of the hippocampal network dentate gyrus, CA3, and CA1 (DG-CA3-CA1) regions. Methods: Computer simulations were made for a pathological model in which Alzheimer's disease was simulated by synaptic degradation in the hippocampus. Pathology modeling was based on sequentially turning off the connections with entorhinal cortex layer 2 (EC2) and the dentate gyrus on CA3 pyramidal neurons. Gamma induction modeling consisted of simulating the oscillation provided by the septo-hippocampal pathway with band frequencies from 40-130 Hz. Pathological models with and without gamma induction were compared with a control. Results: In the hippocampal regions of DG, CA3, and CA1, and jointly DG-CA3-CA1 and CA3-CA1, gamma induction resulted in a statistically significant improvement in terms of increased numbers of spikes, spikes per burst, and burst duration as compared with the model simulating Alzheimer's disease (AD). The positive maximal Lyapunov exponent was negative in both the control model and the one with gamma induction as opposed to the pathological model where it was positive within the DG-CA3-CA1 region. Gamma induction resulted in decreased transfer entropy in accordance with the information flow in DG → CA3 and CA3 → CA1. Conclusions: The results of simulation studies show that inducing gamma oscillations in the hippocampus may reduce Alzheimer's disease related pathology. Pathologically higher transfer entropy values after gamma induction returned to values comparable to the control model.